{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "path = 'E:\\\\HQData\\\\future_basic\\\\'\n",
    "pro = ts.pro_api('0ba8feef618e5db7b1ebb65538fe51e4aef69fb3cbf709d44128f313')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir = \"E:\\\\HQData\\\\future\\\\\"\n",
    "dir_kline = \"E:\\\\HQData\\\\future_klines\\\\\"\n",
    "\n",
    "contracts = list()\n",
    "# 'RM.ZCE'\n",
    "# RB2601.SHF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RB2601.SHF</td>\n",
       "      <td>20250513</td>\n",
       "      <td>3103.0</td>\n",
       "      <td>3066.0</td>\n",
       "      <td>3112.0</td>\n",
       "      <td>3133.0</td>\n",
       "      <td>3086.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>3107.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>33376.0</td>\n",
       "      <td>103716.79</td>\n",
       "      <td>119653.0</td>\n",
       "      <td>5963.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RB2601.SHF</td>\n",
       "      <td>20250512</td>\n",
       "      <td>3037.0</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>3043.0</td>\n",
       "      <td>3105.0</td>\n",
       "      <td>3030.0</td>\n",
       "      <td>3103.0</td>\n",
       "      <td>3066.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>46933.0</td>\n",
       "      <td>143914.53</td>\n",
       "      <td>113690.0</td>\n",
       "      <td>552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RB2601.SHF</td>\n",
       "      <td>20250509</td>\n",
       "      <td>3074.0</td>\n",
       "      <td>3096.0</td>\n",
       "      <td>3069.0</td>\n",
       "      <td>3071.0</td>\n",
       "      <td>3033.0</td>\n",
       "      <td>3037.0</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>-42.0</td>\n",
       "      <td>43518.0</td>\n",
       "      <td>132939.82</td>\n",
       "      <td>113138.0</td>\n",
       "      <td>11140.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ts_code trade_date  pre_close  pre_settle    open    high     low  \\\n",
       "0  RB2601.SHF   20250513     3103.0      3066.0  3112.0  3133.0  3086.0   \n",
       "1  RB2601.SHF   20250512     3037.0      3054.0  3043.0  3105.0  3030.0   \n",
       "2  RB2601.SHF   20250509     3074.0      3096.0  3069.0  3071.0  3033.0   \n",
       "\n",
       "    close  settle  change1  change2      vol     amount        oi   oi_chg  \n",
       "0  3102.0  3107.0     36.0     41.0  33376.0  103716.79  119653.0   5963.0  \n",
       "1  3103.0  3066.0     49.0     12.0  46933.0  143914.53  113690.0    552.0  \n",
       "2  3037.0  3054.0    -59.0    -42.0  43518.0  132939.82  113138.0  11140.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df_rb = pro.fut_daily(ts_code='RB2601.SHF', start_date='20210101', end_date='20251113')\n",
    "df_rb.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir = \"E:\\\\HQData\\\\future\\\\\"\n",
    "\n",
    "df_rb.to_csv(f\"{dir}kline_RB2601.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pro.daily(ts_code='000001.SZ,600000.SH', start_date='20180701', end_date='20180718')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pro.fut_daily(trade_date='20181113', exchange='DCE', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "\n",
    "#获取CU1811合约20180101～20181113期间的行情\n",
    "df = pro.fut_daily(ts_code='CU1811.SHF', start_date='20180101', end_date='20181113')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [ts_code, pre_close, pre_settle, open, high, low, close, settle, change1, change2, vol, amount, oi, oi_chg]\n",
       "Index: []"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pro.fut_daily(ts_code='t01.ZCE', start_date='20180101', end_date='20251125')\n",
    "df['trade_date'] = df['trade_date'].apply(lambda x: datetime.strptime(x,'%Y%m%d'))\n",
    "df = df.set_index('trade_date')\n",
    "df = df.sort_index()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-11-22</th>\n",
       "      <td>RM2201.ZCE</td>\n",
       "      <td>2792.0</td>\n",
       "      <td>2755.0</td>\n",
       "      <td>2770.0</td>\n",
       "      <td>2773.0</td>\n",
       "      <td>2686.0</td>\n",
       "      <td>2710.0</td>\n",
       "      <td>2725.0</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>872706.0</td>\n",
       "      <td>2378402.19</td>\n",
       "      <td>297507.0</td>\n",
       "      <td>-22736.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-23</th>\n",
       "      <td>RM2201.ZCE</td>\n",
       "      <td>2710.0</td>\n",
       "      <td>2725.0</td>\n",
       "      <td>2701.0</td>\n",
       "      <td>2774.0</td>\n",
       "      <td>2683.0</td>\n",
       "      <td>2759.0</td>\n",
       "      <td>2729.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>825137.0</td>\n",
       "      <td>2252200.97</td>\n",
       "      <td>313535.0</td>\n",
       "      <td>16028.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24</th>\n",
       "      <td>RM2201.ZCE</td>\n",
       "      <td>2759.0</td>\n",
       "      <td>2729.0</td>\n",
       "      <td>2757.0</td>\n",
       "      <td>2769.0</td>\n",
       "      <td>2714.0</td>\n",
       "      <td>2764.0</td>\n",
       "      <td>2743.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>914065.0</td>\n",
       "      <td>2507410.11</td>\n",
       "      <td>313264.0</td>\n",
       "      <td>-271.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ts_code  pre_close  pre_settle    open    high     low   close  \\\n",
       "trade_date                                                                      \n",
       "2021-11-22  RM2201.ZCE     2792.0      2755.0  2770.0  2773.0  2686.0  2710.0   \n",
       "2021-11-23  RM2201.ZCE     2710.0      2725.0  2701.0  2774.0  2683.0  2759.0   \n",
       "2021-11-24  RM2201.ZCE     2759.0      2729.0  2757.0  2769.0  2714.0  2764.0   \n",
       "\n",
       "            settle  change1  change2       vol      amount        oi   oi_chg  \n",
       "trade_date                                                                     \n",
       "2021-11-22  2725.0    -45.0    -30.0  872706.0  2378402.19  297507.0 -22736.0  \n",
       "2021-11-23  2729.0     34.0      4.0  825137.0  2252200.97  313535.0  16028.0  \n",
       "2021-11-24  2743.0     35.0     14.0  914065.0  2507410.11  313264.0   -271.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1048</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20210108</td>\n",
       "      <td>2895.0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>2892.0</td>\n",
       "      <td>2928.0</td>\n",
       "      <td>2865.0</td>\n",
       "      <td>2926.0</td>\n",
       "      <td>2894.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>822744.0</td>\n",
       "      <td>2381187.04</td>\n",
       "      <td>402579.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1049</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20210107</td>\n",
       "      <td>2911.0</td>\n",
       "      <td>2893.0</td>\n",
       "      <td>2916.0</td>\n",
       "      <td>2930.0</td>\n",
       "      <td>2875.0</td>\n",
       "      <td>2895.0</td>\n",
       "      <td>2900.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>617490.0</td>\n",
       "      <td>1790486.38</td>\n",
       "      <td>393462.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20210106</td>\n",
       "      <td>2873.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>2877.0</td>\n",
       "      <td>2926.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>2911.0</td>\n",
       "      <td>2893.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>726926.0</td>\n",
       "      <td>2102769.50</td>\n",
       "      <td>399089.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20210105</td>\n",
       "      <td>2872.0</td>\n",
       "      <td>2886.0</td>\n",
       "      <td>2869.0</td>\n",
       "      <td>2885.0</td>\n",
       "      <td>2832.0</td>\n",
       "      <td>2873.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>-25.0</td>\n",
       "      <td>670209.0</td>\n",
       "      <td>1917203.12</td>\n",
       "      <td>385630.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20210104</td>\n",
       "      <td>2883.0</td>\n",
       "      <td>2831.0</td>\n",
       "      <td>2880.0</td>\n",
       "      <td>2922.0</td>\n",
       "      <td>2863.0</td>\n",
       "      <td>2872.0</td>\n",
       "      <td>2886.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>664379.0</td>\n",
       "      <td>1917135.54</td>\n",
       "      <td>392444.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ts_code trade_date  pre_close  pre_settle    open    high     low  \\\n",
       "1048  RM.ZCE   20210108     2895.0      2900.0  2892.0  2928.0  2865.0   \n",
       "1049  RM.ZCE   20210107     2911.0      2893.0  2916.0  2930.0  2875.0   \n",
       "1050  RM.ZCE   20210106     2873.0      2861.0  2877.0  2926.0  2861.0   \n",
       "1051  RM.ZCE   20210105     2872.0      2886.0  2869.0  2885.0  2832.0   \n",
       "1052  RM.ZCE   20210104     2883.0      2831.0  2880.0  2922.0  2863.0   \n",
       "\n",
       "       close  settle  change1  change2       vol      amount        oi oi_chg  \n",
       "1048  2926.0  2894.0     26.0     -6.0  822744.0  2381187.04  402579.0   None  \n",
       "1049  2895.0  2900.0      2.0      7.0  617490.0  1790486.38  393462.0   None  \n",
       "1050  2911.0  2893.0     50.0     32.0  726926.0  2102769.50  399089.0   None  \n",
       "1051  2873.0  2861.0    -13.0    -25.0  670209.0  1917203.12  385630.0   None  \n",
       "1052  2872.0  2886.0     41.0     55.0  664379.0  1917135.54  392444.0   None  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pro.fut_daily(ts_code='RM.ZCE', start_date='20210101', end_date='20251125')\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_ma_sma = get_df_smas(df, [5, 12])\n",
    "plot_curve(df_ma_sma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('E:\\\\HQData\\\\kline_rm.zce.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EG2201.DCE</td>\n",
       "      <td>20211123</td>\n",
       "      <td>5134.0</td>\n",
       "      <td>5089.0</td>\n",
       "      <td>5166.0</td>\n",
       "      <td>5248.0</td>\n",
       "      <td>5116.0</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>5178.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>263255.0</td>\n",
       "      <td>1363265.42</td>\n",
       "      <td>190908.0</td>\n",
       "      <td>-15226.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EG2201.DCE</td>\n",
       "      <td>20211122</td>\n",
       "      <td>5091.0</td>\n",
       "      <td>4992.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>5173.0</td>\n",
       "      <td>4961.0</td>\n",
       "      <td>5134.0</td>\n",
       "      <td>5089.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>331751.0</td>\n",
       "      <td>1688453.37</td>\n",
       "      <td>206134.0</td>\n",
       "      <td>-11459.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EG2201.DCE</td>\n",
       "      <td>20211119</td>\n",
       "      <td>4965.0</td>\n",
       "      <td>5042.0</td>\n",
       "      <td>4965.0</td>\n",
       "      <td>5136.0</td>\n",
       "      <td>4883.0</td>\n",
       "      <td>5091.0</td>\n",
       "      <td>4992.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>-50.0</td>\n",
       "      <td>396160.0</td>\n",
       "      <td>1977926.74</td>\n",
       "      <td>217593.0</td>\n",
       "      <td>2974.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EG2201.DCE</td>\n",
       "      <td>20211118</td>\n",
       "      <td>5116.0</td>\n",
       "      <td>5101.0</td>\n",
       "      <td>5110.0</td>\n",
       "      <td>5128.0</td>\n",
       "      <td>4952.0</td>\n",
       "      <td>4965.0</td>\n",
       "      <td>5042.0</td>\n",
       "      <td>-136.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>386237.0</td>\n",
       "      <td>1947607.52</td>\n",
       "      <td>214619.0</td>\n",
       "      <td>10862.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EG2201.DCE</td>\n",
       "      <td>20211117</td>\n",
       "      <td>5208.0</td>\n",
       "      <td>5174.0</td>\n",
       "      <td>5190.0</td>\n",
       "      <td>5203.0</td>\n",
       "      <td>5044.0</td>\n",
       "      <td>5116.0</td>\n",
       "      <td>5101.0</td>\n",
       "      <td>-58.0</td>\n",
       "      <td>-73.0</td>\n",
       "      <td>422451.0</td>\n",
       "      <td>2155322.91</td>\n",
       "      <td>203757.0</td>\n",
       "      <td>16125.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ts_code trade_date  pre_close  pre_settle    open    high     low  \\\n",
       "0  EG2201.DCE   20211123     5134.0      5089.0  5166.0  5248.0  5116.0   \n",
       "1  EG2201.DCE   20211122     5091.0      4992.0  5000.0  5173.0  4961.0   \n",
       "2  EG2201.DCE   20211119     4965.0      5042.0  4965.0  5136.0  4883.0   \n",
       "3  EG2201.DCE   20211118     5116.0      5101.0  5110.0  5128.0  4952.0   \n",
       "4  EG2201.DCE   20211117     5208.0      5174.0  5190.0  5203.0  5044.0   \n",
       "\n",
       "    close  settle  change1  change2       vol      amount        oi   oi_chg  \n",
       "0  5200.0  5178.0    111.0     89.0  263255.0  1363265.42  190908.0 -15226.0  \n",
       "1  5134.0  5089.0    142.0     97.0  331751.0  1688453.37  206134.0 -11459.0  \n",
       "2  5091.0  4992.0     49.0    -50.0  396160.0  1977926.74  217593.0   2974.0  \n",
       "3  4965.0  5042.0   -136.0    -59.0  386237.0  1947607.52  214619.0  10862.0  \n",
       "4  5116.0  5101.0    -58.0    -73.0  422451.0  2155322.91  203757.0  16125.0  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pro.fut_daily(ts_code='EG2201.DCE', start_date='20180101', end_date='20211125')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>change1</th>\n",
       "      <th>change2</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>oi</th>\n",
       "      <th>oi_chg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>940</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20180108</td>\n",
       "      <td>2293.0</td>\n",
       "      <td>2287.0</td>\n",
       "      <td>2299.0</td>\n",
       "      <td>2301.0</td>\n",
       "      <td>2280.0</td>\n",
       "      <td>2280.0</td>\n",
       "      <td>2289.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>354590.0</td>\n",
       "      <td>811651.53</td>\n",
       "      <td>612182.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>941</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20180105</td>\n",
       "      <td>2283.0</td>\n",
       "      <td>2288.0</td>\n",
       "      <td>2282.0</td>\n",
       "      <td>2302.0</td>\n",
       "      <td>2271.0</td>\n",
       "      <td>2293.0</td>\n",
       "      <td>2287.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>494790.0</td>\n",
       "      <td>1131521.86</td>\n",
       "      <td>614906.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>942</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20180104</td>\n",
       "      <td>2294.0</td>\n",
       "      <td>2295.0</td>\n",
       "      <td>2297.0</td>\n",
       "      <td>2298.0</td>\n",
       "      <td>2276.0</td>\n",
       "      <td>2283.0</td>\n",
       "      <td>2288.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>410686.0</td>\n",
       "      <td>939508.78</td>\n",
       "      <td>625648.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20180103</td>\n",
       "      <td>2288.0</td>\n",
       "      <td>2291.0</td>\n",
       "      <td>2290.0</td>\n",
       "      <td>2303.0</td>\n",
       "      <td>2288.0</td>\n",
       "      <td>2294.0</td>\n",
       "      <td>2295.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>331632.0</td>\n",
       "      <td>761093.01</td>\n",
       "      <td>608344.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20180102</td>\n",
       "      <td>2290.0</td>\n",
       "      <td>2310.0</td>\n",
       "      <td>2302.0</td>\n",
       "      <td>2306.0</td>\n",
       "      <td>2279.0</td>\n",
       "      <td>2288.0</td>\n",
       "      <td>2291.0</td>\n",
       "      <td>-22.0</td>\n",
       "      <td>-19.0</td>\n",
       "      <td>276174.0</td>\n",
       "      <td>632713.23</td>\n",
       "      <td>606340.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ts_code trade_date  pre_close  pre_settle    open    high     low   close  \\\n",
       "940  RM.ZCE   20180108     2293.0      2287.0  2299.0  2301.0  2280.0  2280.0   \n",
       "941  RM.ZCE   20180105     2283.0      2288.0  2282.0  2302.0  2271.0  2293.0   \n",
       "942  RM.ZCE   20180104     2294.0      2295.0  2297.0  2298.0  2276.0  2283.0   \n",
       "943  RM.ZCE   20180103     2288.0      2291.0  2290.0  2303.0  2288.0  2294.0   \n",
       "944  RM.ZCE   20180102     2290.0      2310.0  2302.0  2306.0  2279.0  2288.0   \n",
       "\n",
       "     settle  change1  change2       vol      amount        oi oi_chg  \n",
       "940  2289.0     -7.0      2.0  354590.0   811651.53  612182.0   None  \n",
       "941  2287.0      5.0     -1.0  494790.0  1131521.86  614906.0   None  \n",
       "942  2288.0    -12.0     -7.0  410686.0   939508.78  625648.0   None  \n",
       "943  2295.0      3.0      4.0  331632.0   761093.01  608344.0   None  \n",
       "944  2291.0    -22.0    -19.0  276174.0   632713.23  606340.0   None  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def get_df_smas(df, lenthlist):\n",
    "    df_temp = pd.DataFrame(df['close'])\n",
    "    for i in lenthlist:\n",
    "        df_temp['sma_'+ str(i)] = ta.SMA(df['close'], i)\n",
    "    \n",
    "    return df_temp\n",
    "\n",
    "def get_day_bbands(df):\n",
    "    df_bbands = pd.DataFrame(df['close'])\n",
    "    df_bbands['upper'], df_bbands['middle'], df_bbands['lower'] = ta.BBANDS(\n",
    "                df.close, \n",
    "                timeperiod=10,\n",
    "                # number of non-biased standard deviations from the mean\n",
    "                nbdevup= 2,\n",
    "                nbdevdn= 2,\n",
    "                # Moving average type: simple moving average here\n",
    "                matype=0)\n",
    "    df_bbands['signal_B'] = df_bbands['close'] <= df_bbands['lower']\n",
    "    df_bbands['signal_S'] = df_bbands['close'] >= df_bbands['upper']\n",
    "    return df_bbands\n",
    "\n",
    "\n",
    "def plot_curve(plot_dict):\n",
    "    \"\"\"\n",
    "    plot the net asset value curve\n",
    "    :param plot_dict: type--dict, {label name (str): time series data (pd.Series)}\n",
    "    :return: None\n",
    "    \"\"\"\n",
    "    import matplotlib.pyplot as plt\n",
    "    fig, ax = plt.subplots(figsize=(28, 8))\n",
    "    fig.patch.set_facecolor('white')\n",
    "    transparency_level = 1.\n",
    "    \n",
    "    for _ts_label, _ts_curve in plot_dict.items():\n",
    "        _ts_curve.plot(ax=ax, lw=1.5, label=_ts_label, alpha=transparency_level)\n",
    "    \n",
    "    ax.legend(loc='upper left', shadow=True)    \n",
    "\n",
    "    plt.show() \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ma_sma = get_df_smas(df, [5, 10])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_ma_sma = df_ma_sma.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>sma_5</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5586.0</td>\n",
       "      <td>5641.8</td>\n",
       "      <td>5576.1</td>\n",
       "      <td>5384.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6071.0</td>\n",
       "      <td>5714.0</td>\n",
       "      <td>5642.2</td>\n",
       "      <td>5428.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>6257.0</td>\n",
       "      <td>5833.6</td>\n",
       "      <td>5720.1</td>\n",
       "      <td>5484.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6303.0</td>\n",
       "      <td>5998.0</td>\n",
       "      <td>5809.3</td>\n",
       "      <td>5545.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>6507.0</td>\n",
       "      <td>6144.8</td>\n",
       "      <td>5903.7</td>\n",
       "      <td>5622.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     close   sma_5  sma_10   sma_20\n",
       "19  5586.0  5641.8  5576.1  5384.80\n",
       "20  6071.0  5714.0  5642.2  5428.35\n",
       "21  6257.0  5833.6  5720.1  5484.50\n",
       "22  6303.0  5998.0  5809.3  5545.10\n",
       "23  6507.0  6144.8  5903.7  5622.20"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ma_sma.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_curve(df_ma_sma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['close'].plot(figsize=(16,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_ma_sma = get_df_smas(df, [5, 12])\n",
    "plot_curve(df_ma_sma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ma_sma.to_csv('analy_eg.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pro.fut_daily(trade_date='20250709', exchange='DCE', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4104.0</td>\n",
       "      <td>4090.0</td>\n",
       "      <td>4103.0</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>4098.0</td>\n",
       "      <td>4111.0</td>\n",
       "      <td>4112.0</td>\n",
       "      <td>97142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A2507.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A2509.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4104.0</td>\n",
       "      <td>4090.0</td>\n",
       "      <td>4103.0</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>4098.0</td>\n",
       "      <td>4111.0</td>\n",
       "      <td>4112.0</td>\n",
       "      <td>97142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A2511.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4042.0</td>\n",
       "      <td>4037.0</td>\n",
       "      <td>4042.0</td>\n",
       "      <td>4056.0</td>\n",
       "      <td>4038.0</td>\n",
       "      <td>4045.0</td>\n",
       "      <td>4048.0</td>\n",
       "      <td>20023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A2601.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4030.0</td>\n",
       "      <td>4022.0</td>\n",
       "      <td>4029.0</td>\n",
       "      <td>4043.0</td>\n",
       "      <td>4026.0</td>\n",
       "      <td>4029.0</td>\n",
       "      <td>4033.0</td>\n",
       "      <td>5029.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>Y2512.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>7992.0</td>\n",
       "      <td>7972.0</td>\n",
       "      <td>7964.0</td>\n",
       "      <td>7980.0</td>\n",
       "      <td>7956.0</td>\n",
       "      <td>7972.0</td>\n",
       "      <td>7962.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Y2601.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>7940.0</td>\n",
       "      <td>7910.0</td>\n",
       "      <td>7928.0</td>\n",
       "      <td>7934.0</td>\n",
       "      <td>7900.0</td>\n",
       "      <td>7916.0</td>\n",
       "      <td>7916.0</td>\n",
       "      <td>63790.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>Y2603.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>7850.0</td>\n",
       "      <td>7820.0</td>\n",
       "      <td>7822.0</td>\n",
       "      <td>7830.0</td>\n",
       "      <td>7806.0</td>\n",
       "      <td>7826.0</td>\n",
       "      <td>7818.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>Y2605.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>7634.0</td>\n",
       "      <td>7612.0</td>\n",
       "      <td>7622.0</td>\n",
       "      <td>7626.0</td>\n",
       "      <td>7578.0</td>\n",
       "      <td>7604.0</td>\n",
       "      <td>7594.0</td>\n",
       "      <td>6668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>YL.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>8038.0</td>\n",
       "      <td>8038.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8038.0</td>\n",
       "      <td>8038.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>269 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date  pre_close  pre_settle    open    high     low  \\\n",
       "0        A.DCE   20250709     4104.0      4090.0  4103.0  4120.0  4098.0   \n",
       "1    A2507.DCE   20250709     4150.0      4150.0     NaN     NaN     NaN   \n",
       "2    A2509.DCE   20250709     4104.0      4090.0  4103.0  4120.0  4098.0   \n",
       "3    A2511.DCE   20250709     4042.0      4037.0  4042.0  4056.0  4038.0   \n",
       "4    A2601.DCE   20250709     4030.0      4022.0  4029.0  4043.0  4026.0   \n",
       "..         ...        ...        ...         ...     ...     ...     ...   \n",
       "264  Y2512.DCE   20250709     7992.0      7972.0  7964.0  7980.0  7956.0   \n",
       "265  Y2601.DCE   20250709     7940.0      7910.0  7928.0  7934.0  7900.0   \n",
       "266  Y2603.DCE   20250709     7850.0      7820.0  7822.0  7830.0  7806.0   \n",
       "267  Y2605.DCE   20250709     7634.0      7612.0  7622.0  7626.0  7578.0   \n",
       "268     YL.DCE   20250709     8038.0      8038.0     NaN     NaN     NaN   \n",
       "\n",
       "      close  settle      vol  \n",
       "0    4111.0  4112.0  97142.0  \n",
       "1    4150.0  4150.0      0.0  \n",
       "2    4111.0  4112.0  97142.0  \n",
       "3    4045.0  4048.0  20023.0  \n",
       "4    4029.0  4033.0   5029.0  \n",
       "..      ...     ...      ...  \n",
       "264  7972.0  7962.0     26.0  \n",
       "265  7916.0  7916.0  63790.0  \n",
       "266  7826.0  7818.0     32.0  \n",
       "267  7604.0  7594.0   6668.0  \n",
       "268  8038.0  8038.0      0.0  \n",
       "\n",
       "[269 rows x 10 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4104.0</td>\n",
       "      <td>4090.0</td>\n",
       "      <td>4103.0</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>4098.0</td>\n",
       "      <td>4111.0</td>\n",
       "      <td>4112.0</td>\n",
       "      <td>97142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A2507.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>4150.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A2509.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4104.0</td>\n",
       "      <td>4090.0</td>\n",
       "      <td>4103.0</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>4098.0</td>\n",
       "      <td>4111.0</td>\n",
       "      <td>4112.0</td>\n",
       "      <td>97142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A2511.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4042.0</td>\n",
       "      <td>4037.0</td>\n",
       "      <td>4042.0</td>\n",
       "      <td>4056.0</td>\n",
       "      <td>4038.0</td>\n",
       "      <td>4045.0</td>\n",
       "      <td>4048.0</td>\n",
       "      <td>20023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A2601.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4030.0</td>\n",
       "      <td>4022.0</td>\n",
       "      <td>4029.0</td>\n",
       "      <td>4043.0</td>\n",
       "      <td>4026.0</td>\n",
       "      <td>4029.0</td>\n",
       "      <td>4033.0</td>\n",
       "      <td>5029.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>ZN2603.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>21730.0</td>\n",
       "      <td>21705.0</td>\n",
       "      <td>21810.0</td>\n",
       "      <td>21880.0</td>\n",
       "      <td>21750.0</td>\n",
       "      <td>21790.0</td>\n",
       "      <td>21795.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>ZN2604.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>21730.0</td>\n",
       "      <td>21675.0</td>\n",
       "      <td>21740.0</td>\n",
       "      <td>21885.0</td>\n",
       "      <td>21740.0</td>\n",
       "      <td>21810.0</td>\n",
       "      <td>21790.0</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>ZN2605.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>21715.0</td>\n",
       "      <td>21660.0</td>\n",
       "      <td>21800.0</td>\n",
       "      <td>21890.0</td>\n",
       "      <td>21740.0</td>\n",
       "      <td>21845.0</td>\n",
       "      <td>21800.0</td>\n",
       "      <td>172.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>ZN2606.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>21700.0</td>\n",
       "      <td>21640.0</td>\n",
       "      <td>21720.0</td>\n",
       "      <td>21875.0</td>\n",
       "      <td>21715.0</td>\n",
       "      <td>21815.0</td>\n",
       "      <td>21790.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>ZNL.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>22070.0</td>\n",
       "      <td>22020.0</td>\n",
       "      <td>22160.0</td>\n",
       "      <td>22165.0</td>\n",
       "      <td>22010.0</td>\n",
       "      <td>22100.0</td>\n",
       "      <td>22100.0</td>\n",
       "      <td>1280.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>997 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ts_code trade_date  pre_close  pre_settle     open     high      low  \\\n",
       "0         A.DCE   20250709     4104.0      4090.0   4103.0   4120.0   4098.0   \n",
       "1     A2507.DCE   20250709     4150.0      4150.0      NaN      NaN      NaN   \n",
       "2     A2509.DCE   20250709     4104.0      4090.0   4103.0   4120.0   4098.0   \n",
       "3     A2511.DCE   20250709     4042.0      4037.0   4042.0   4056.0   4038.0   \n",
       "4     A2601.DCE   20250709     4030.0      4022.0   4029.0   4043.0   4026.0   \n",
       "..          ...        ...        ...         ...      ...      ...      ...   \n",
       "992  ZN2603.SHF   20250709    21730.0     21705.0  21810.0  21880.0  21750.0   \n",
       "993  ZN2604.SHF   20250709    21730.0     21675.0  21740.0  21885.0  21740.0   \n",
       "994  ZN2605.SHF   20250709    21715.0     21660.0  21800.0  21890.0  21740.0   \n",
       "995  ZN2606.SHF   20250709    21700.0     21640.0  21720.0  21875.0  21715.0   \n",
       "996     ZNL.SHF   20250709    22070.0     22020.0  22160.0  22165.0  22010.0   \n",
       "\n",
       "       close   settle      vol  \n",
       "0     4111.0   4112.0  97142.0  \n",
       "1     4150.0   4150.0      0.0  \n",
       "2     4111.0   4112.0  97142.0  \n",
       "3     4045.0   4048.0  20023.0  \n",
       "4     4029.0   4033.0   5029.0  \n",
       "..       ...      ...      ...  \n",
       "992  21790.0  21795.0    126.0  \n",
       "993  21810.0  21790.0    113.0  \n",
       "994  21845.0  21800.0    172.0  \n",
       "995  21815.0  21790.0     69.0  \n",
       "996  22100.0  22100.0   1280.0  \n",
       "\n",
       "[997 rows x 10 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pro.fut_daily(trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2.to_csv(dir+\"tradedate0709.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EG.DCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>4267.0</td>\n",
       "      <td>4273.0</td>\n",
       "      <td>4270.0</td>\n",
       "      <td>4291.0</td>\n",
       "      <td>4261.0</td>\n",
       "      <td>4283.0</td>\n",
       "      <td>4275.0</td>\n",
       "      <td>119519.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FG.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>1024.0</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>1037.0</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>1035.0</td>\n",
       "      <td>1029.0</td>\n",
       "      <td>1216517.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RB.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>3063.0</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>3077.0</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>3063.0</td>\n",
       "      <td>3065.0</td>\n",
       "      <td>1026448.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>2576.0</td>\n",
       "      <td>2581.0</td>\n",
       "      <td>2568.0</td>\n",
       "      <td>2595.0</td>\n",
       "      <td>2548.0</td>\n",
       "      <td>2586.0</td>\n",
       "      <td>2573.0</td>\n",
       "      <td>280603.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SA.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1177.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>1175.0</td>\n",
       "      <td>1194.0</td>\n",
       "      <td>1187.0</td>\n",
       "      <td>1475079.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ts_code trade_date  pre_close  pre_settle    open    high     low   close  \\\n",
       "0  EG.DCE   20250709     4267.0      4273.0  4270.0  4291.0  4261.0  4283.0   \n",
       "1  FG.ZCE   20250709     1025.0      1024.0  1026.0  1037.0  1020.0  1035.0   \n",
       "2  RB.SHF   20250709     3063.0      3061.0  3061.0  3077.0  3054.0  3063.0   \n",
       "3  RM.ZCE   20250709     2576.0      2581.0  2568.0  2595.0  2548.0  2586.0   \n",
       "4  SA.ZCE   20250709     1178.0      1177.0  1178.0  1198.0  1175.0  1194.0   \n",
       "\n",
       "   settle        vol  \n",
       "0  4275.0   119519.0  \n",
       "1  1029.0  1216517.0  \n",
       "2  3065.0  1026448.0  \n",
       "3  2573.0   280603.0  \n",
       "4  1187.0  1475079.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = pro.fut_daily(ts_code = 'SA.ZCE,RM.ZCE,RB.SHF,EG.DCE,FG.ZCE', trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'SA.ZCE, RB.SHF, RM.ZCE'\n"
     ]
    }
   ],
   "source": [
    "print(f\"\\'{', '.join( x for x in ['SA.ZCE','RB.SHF','RM.ZCE'])}\\'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'SA.ZCE,RB.SHF,RM.ZCE'\n"
     ]
    }
   ],
   "source": [
    "print(tscode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SA.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1177.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>1175.0</td>\n",
       "      <td>1194.0</td>\n",
       "      <td>1187.0</td>\n",
       "      <td>1475079.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ts_code trade_date  pre_close  pre_settle    open    high     low   close  \\\n",
       "0  SA.ZCE   20250709     1178.0      1177.0  1178.0  1198.0  1175.0  1194.0   \n",
       "\n",
       "   settle        vol  \n",
       "0  1187.0  1475079.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5 = pro.fut_daily(ts_code = ', '.join( x for x in ['SA.ZCE','RB.SHF','RM.ZCE']), trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [ts_code, trade_date, pre_close, pre_settle, open, high, low, close, settle, vol]\n",
       "Index: []"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5 = pro.fut_daily(ts_code = ['SA.ZCE','RB.SHF','RM.ZCE'], trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'SA.ZCE,RB.SHF,RM.ZCE'\n"
     ]
    },
    {
     "ename": "Exception",
     "evalue": "警告！存在恶意行为，将会禁用您的账号。",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mException\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[33], line 3\u001b[0m\n\u001b[0;32m      1\u001b[0m tscode \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;250m \u001b[39mx\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mx\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSA.ZCE\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRB.SHF\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRM.ZCE\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28mprint\u001b[39m(tscode)\n\u001b[1;32m----> 3\u001b[0m df5 \u001b[38;5;241m=\u001b[39m \u001b[43mpro\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfut_daily\u001b[49m\u001b[43m(\u001b[49m\u001b[43mts_code\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mtscode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrade_date\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m20250709\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfields\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      4\u001b[0m df5\n",
      "File \u001b[1;32mD:\\ProgramData\\anaconda3\\envs\\trader\\lib\\site-packages\\tushare\\pro\\client.py:45\u001b[0m, in \u001b[0;36mDataApi.query\u001b[1;34m(self, api_name, fields, **kwargs)\u001b[0m\n\u001b[0;32m     43\u001b[0m result \u001b[38;5;241m=\u001b[39m json\u001b[38;5;241m.\u001b[39mloads(res\u001b[38;5;241m.\u001b[39mtext)\n\u001b[0;32m     44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcode\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m---> 45\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmsg\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m     46\u001b[0m data \u001b[38;5;241m=\u001b[39m result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m     47\u001b[0m columns \u001b[38;5;241m=\u001b[39m data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfields\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
      "\u001b[1;31mException\u001b[0m: 警告！存在恶意行为，将会禁用您的账号。"
     ]
    }
   ],
   "source": [
    "tscode = f\"\\'{','.join( x for x in ['SA.ZCE','RB.SHF','RM.ZCE'])}\\'\"\n",
    "print(tscode)\n",
    "df5 = pro.fut_daily(ts_code = tscode, trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RB.SHF</td>\n",
       "      <td>20250709</td>\n",
       "      <td>3063.0</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>3061.0</td>\n",
       "      <td>3077.0</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>3063.0</td>\n",
       "      <td>3065.0</td>\n",
       "      <td>1026448.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RM.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>2576.0</td>\n",
       "      <td>2581.0</td>\n",
       "      <td>2568.0</td>\n",
       "      <td>2595.0</td>\n",
       "      <td>2548.0</td>\n",
       "      <td>2586.0</td>\n",
       "      <td>2573.0</td>\n",
       "      <td>280603.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SA.ZCE</td>\n",
       "      <td>20250709</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1177.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>1198.0</td>\n",
       "      <td>1175.0</td>\n",
       "      <td>1194.0</td>\n",
       "      <td>1187.0</td>\n",
       "      <td>1475079.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ts_code trade_date  pre_close  pre_settle    open    high     low   close  \\\n",
       "0  RB.SHF   20250709     3063.0      3061.0  3061.0  3077.0  3054.0  3063.0   \n",
       "1  RM.ZCE   20250709     2576.0      2581.0  2568.0  2595.0  2548.0  2586.0   \n",
       "2  SA.ZCE   20250709     1178.0      1177.0  1178.0  1198.0  1175.0  1194.0   \n",
       "\n",
       "   settle        vol  \n",
       "0  3065.0  1026448.0  \n",
       "1  2573.0   280603.0  \n",
       "2  1187.0  1475079.0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df5 = pro.fut_daily(ts_code = tscode1, trade_date='20250709', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "tscode1 = f\"{','.join( x for x in ['SA.ZCE','RB.SHF','RM.ZCE'])}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('ts_code', 0    RB.SHF\n",
      "1    RM.ZCE\n",
      "2    SA.ZCE\n",
      "Name: ts_code, dtype: object)\n",
      "<class 'tuple'>\n",
      "('trade_date', 0    20250709\n",
      "1    20250709\n",
      "2    20250709\n",
      "Name: trade_date, dtype: object)\n",
      "<class 'tuple'>\n",
      "('pre_close', 0    3063.0\n",
      "1    2576.0\n",
      "2    1178.0\n",
      "Name: pre_close, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('pre_settle', 0    3061.0\n",
      "1    2581.0\n",
      "2    1177.0\n",
      "Name: pre_settle, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('open', 0    3061.0\n",
      "1    2568.0\n",
      "2    1178.0\n",
      "Name: open, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('high', 0    3077.0\n",
      "1    2595.0\n",
      "2    1198.0\n",
      "Name: high, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('low', 0    3054.0\n",
      "1    2548.0\n",
      "2    1175.0\n",
      "Name: low, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('close', 0    3063.0\n",
      "1    2586.0\n",
      "2    1194.0\n",
      "Name: close, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('settle', 0    3065.0\n",
      "1    2573.0\n",
      "2    1187.0\n",
      "Name: settle, dtype: float64)\n",
      "<class 'tuple'>\n",
      "('vol', 0    1026448.0\n",
      "1     280603.0\n",
      "2    1475079.0\n",
      "Name: vol, dtype: float64)\n",
      "<class 'tuple'>\n"
     ]
    }
   ],
   "source": [
    "for item in df5.items():\n",
    "    print(item)\n",
    "    print(type(item))\n",
    "    # print(''.join(x for x in item))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ts_code\n",
      "-----\n",
      "trade_date\n",
      "-----\n",
      "pre_close\n",
      "-----\n",
      "pre_settle\n",
      "-----\n",
      "open\n",
      "-----\n",
      "high\n",
      "-----\n",
      "low\n",
      "-----\n",
      "close\n",
      "-----\n",
      "settle\n",
      "-----\n",
      "vol\n",
      "-----\n"
     ]
    }
   ],
   "source": [
    "for column in df5.columns:\n",
    "    print(column)\n",
    "    print(\"-----\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('ts_code', 0    RB.SHF\n",
      "1    RM.ZCE\n",
      "2    SA.ZCE\n",
      "Name: ts_code, dtype: object)\n",
      "-----\n",
      "('trade_date', 0    20250709\n",
      "1    20250709\n",
      "2    20250709\n",
      "Name: trade_date, dtype: object)\n",
      "-----\n",
      "('pre_close', 0    3063.0\n",
      "1    2576.0\n",
      "2    1178.0\n",
      "Name: pre_close, dtype: float64)\n",
      "-----\n",
      "('pre_settle', 0    3061.0\n",
      "1    2581.0\n",
      "2    1177.0\n",
      "Name: pre_settle, dtype: float64)\n",
      "-----\n",
      "('open', 0    3061.0\n",
      "1    2568.0\n",
      "2    1178.0\n",
      "Name: open, dtype: float64)\n",
      "-----\n",
      "('high', 0    3077.0\n",
      "1    2595.0\n",
      "2    1198.0\n",
      "Name: high, dtype: float64)\n",
      "-----\n",
      "('low', 0    3054.0\n",
      "1    2548.0\n",
      "2    1175.0\n",
      "Name: low, dtype: float64)\n",
      "-----\n",
      "('close', 0    3063.0\n",
      "1    2586.0\n",
      "2    1194.0\n",
      "Name: close, dtype: float64)\n",
      "-----\n",
      "('settle', 0    3065.0\n",
      "1    2573.0\n",
      "2    1187.0\n",
      "Name: settle, dtype: float64)\n",
      "-----\n",
      "('vol', 0    1026448.0\n",
      "1     280603.0\n",
      "2    1475079.0\n",
      "Name: vol, dtype: float64)\n",
      "-----\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_6248\\443573113.py:1: FutureWarning: iteritems is deprecated and will be removed in a future version. Use .items instead.\n",
      "  for column in df5.iteritems():\n"
     ]
    }
   ],
   "source": [
    "\n",
    "  for column in df5.iteritems():\n",
    "    print(column)  \n",
    "    print(\"-----\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, ts_code          RB.SHF\n",
      "trade_date     20250709\n",
      "pre_close        3063.0\n",
      "pre_settle       3061.0\n",
      "open             3061.0\n",
      "high             3077.0\n",
      "low              3054.0\n",
      "close            3063.0\n",
      "settle           3065.0\n",
      "vol           1026448.0\n",
      "Name: 0, dtype: object)\n",
      "-----\n",
      "(1, ts_code         RM.ZCE\n",
      "trade_date    20250709\n",
      "pre_close       2576.0\n",
      "pre_settle      2581.0\n",
      "open            2568.0\n",
      "high            2595.0\n",
      "low             2548.0\n",
      "close           2586.0\n",
      "settle          2573.0\n",
      "vol           280603.0\n",
      "Name: 1, dtype: object)\n",
      "-----\n",
      "(2, ts_code          SA.ZCE\n",
      "trade_date     20250709\n",
      "pre_close        1178.0\n",
      "pre_settle       1177.0\n",
      "open             1178.0\n",
      "high             1198.0\n",
      "low              1175.0\n",
      "close            1194.0\n",
      "settle           1187.0\n",
      "vol           1475079.0\n",
      "Name: 2, dtype: object)\n",
      "-----\n"
     ]
    }
   ],
   "source": [
    "\n",
    "  for row in df5.iterrows():\n",
    "    print(row)  \n",
    "    print(\"-----\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RB.SHF,o:3061.0,h:3077.0,l:3054.0,c:3063.0,v:1026448.0\n",
      "-----\n",
      "RM.ZCE,o:2568.0,h:2595.0,l:2548.0,c:2586.0,v:280603.0\n",
      "-----\n",
      "SA.ZCE,o:1178.0,h:1198.0,l:1175.0,c:1194.0,v:1475079.0\n",
      "-----\n"
     ]
    }
   ],
   "source": [
    "\n",
    "  for row in df5.iterrows():\n",
    "    print(f\"{row[1]['ts_code']},o:{row[1]['open']},h:{row[1]['high']},l:{row[1]['low']},c:{row[1]['close']},v:{row[1]['vol']}\") \n",
    "    print(\"-----\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>pre_settle</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>settle</th>\n",
       "      <th>vol</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [ts_code, trade_date, pre_close, pre_settle, open, high, low, close, settle, vol]\n",
       "Index: []"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df6 = pro.fut_daily(ts_code = tscode1, trade_date='20250712', fields='ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,vol')\n",
    "df6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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